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Video Transcript:

This is an overview of the Dreamdata platform that will turn the data scattered across your tech stack into an organised data set that you can base your B2B revenue analytics and operations on.

When connecting your tech stack to Dreamdata we extract data from all the individual tools such as CRM, automation, helpdesk, ad platforms. We also collect behaviour tracking from things like your website and apps.

To unlock the potential of this data, we need to organise the different data sources to make a single coherent data set to base insight and modelling on.

We first clean the different sources by removing irrelevant and duplicated data. 

We enrich using things like firmographics.

Next, we standardise across sources to allow us to join together activities across sources and tools. 

So we can turn all the user interactions into well-defined sessions.

We glue these sessions from individual users together into accounts. This is a crucial step for allowing B2B analytics, as behaviour is on a user level, but we are selling on an account level. 

Finally, we connect each account journey to revenue and pipeline stages defined by your CRM.

We now know what each individual person and account did before they reached certain pipeline stages. So we can now turn to multitouch attribution models. 

We build all the common multitouch models out-of-the-box.

We allow for more advanced settings like ranking, exclusion or fully customized multitouch models.

Both the transformed and the modelled data now sit in organised tables ready to be activated. 

This can be done through the Dreamdata app where we have collected commonly used analyses ready and available.

We constantly improve these and add to them based on best practices.

However, we realise that sometimes you might want to do something customized to your business problem. 

That is why all the data tables that power the Dreamdata application are made available for you in BigQuery. 

They can then be used in your favourite BI tool or other operational systems. Or you can use it to power your own ML models.

 
All in all the data platform makes organised data available from across your tech stack, without you having to set up a complex data transformation and orchestration pipeline.


Find out more about Dreamdata’s data platform here.